A multi source product reputation model

Product reputation model is very important for customers and manufacturers in order to make decisions. Several product reputation models are proposed in literature which use customer reviews in order to compute reputation values. However, the aggregation methods used are not able to estimate a good reputation value when some ratings are false. Some of these aggregation methods are not robust to false and biased ratings because a single false rating is enough to change the result. Others are robust to false ratings but not able to reflect the recent opinions about product quickly. In addition, most of the product reputation models are based on single source, therefore suffer from availability and vulnerability issues. In this paper, we propose a multi-source product reputation model where robust and strategy proof aggregation methods are used. A source credibility measure method is proposed, which uses four factors to determine malicious sources. Furthermore, a suitable decay principle for product reputation is also introduced in order to reflect the newest opinions quickly. The results show that proposed model is robust, strategy proof and able to provide a good estimation even if some ratings are false.